Computerized tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), coupled with developments in computer-based image processing and modeling capabilities have led to significant improvements in the ability to visualize anatomical structures in human patients. This information has become invaluable in the diagnosis, treatment, and tracking of patients. The technology has been recently been expanded to be used in conjunction with real-time interventional procedures.
MRI is the method of creating images (referred to as MR images) of the internal organs in living organisms. The primary purpose is demonstrating pathological or other physiological alterations of living tissues. MRI has also found many niche applications outside of the medical and biological fields such as rock permeability to hydrocarbons and certain non-destructive testing methods such as produce and timber quality characterization. Superb image contrast for soft tissues and millimeter scale spatial resolution has established MRI as a core imaging technology in most medical centers. MRI is unique among imaging modalities in that any one of a multitude of tissue properties can be extracted and highlighted.
The MRI process requires a highly accurate and stable target which to image. This is a consequence of the process by which medical MRI functions. Medical MRI most frequently relies on the relaxation properties of excited hydrogen nuclei in water. When the object to be imaged is placed in a powerful, uniform magnetic field, the spins of the atomic nuclei with non-zero spin numbers within the tissue all align in one of two opposite directions: parallel to the magnetic field or antiparallel.
The difference in the number of parallel and antiparallel nuclei is only about one in a million. However, due to the vast quantity of nuclei in a small volume, the nuclei sum to produce a detectable change in field strength. The magnetic dipole moment of the nuclei then moves in a gyrating fashion around the axial field. While the proportion is nearly equal, slightly more nuclei are oriented at the low energy angle. The frequency with which the dipole moments process is called the Larmor frequency. The tissue is then briefly exposed to pulses of electromagnetic energy (RF pulse) in a plane perpendicular to the magnetic field, causing some of the magnetically aligned hydrogen nuclei to assume a temporary non-aligned high-energy state.
In order to selectively image the different voxels (3-D pixels) of the material in question, three orthogonal magnetic gradients are applied. The first is the slice selection, which is applied during the RF pulse. Next comes the phase encoding gradient, and finally the frequency encoding gradient, during which the tissue is imaged. Most of the time, the three gradients are applied in the X, Y, and Z directions of the machine. As a consequence of this methodology, any small shift in the position of the patient with respect to these fixed gradient axes will alter the orientations and positions of the selected slices.
In order to create an MR image, spatial information must be recorded along with the received tissue relaxation information. For this reason, magnetic fields with an intensity gradient are applied in addition to the strong alignment field to allow encoding of the position of the nuclei. A field with the gradient increasing in each of the three dimensional planes is applied in sequence. This information is then subsequently subjected to a Fourier transformation by a computer that transforms the data into the desired image and yields detailed anatomical information results.
With conventional anatomic MR imaging, the presence of moving biological tissue is problematic. The tissue produces image artifacts, degrades the quality of the images, and complicates the interpretation of MR images. The typical appearance of such image artifacts takes the form of “blurring,” or a characteristic “motion ghost” in the phase encoding direction associated with incorrectly encoding the spatial frequencies of a moving object that is assumed to be static.
The typical medical resolution is about 1 mm, while research models can exceed 0.1 mm. Through the process of MRI, anatomy can be defined in great detail, and several other biophysical and metabolic properties of tissue, including blood flow, blood volume, elasticity, oxygenation, permeability, molecular self-diffusion, anisotropy, and water exchange through cell membranes, can also be represented. Conventional anatomical MR imaging uses this spin-echo, gradient-echo, and inversion recovery sequencing. There are other methods of MR that are currently being used, including magnetic resonance spectroscopy (MRS), apparent diffusion coefficient (ADC) mapping, diffusion-weighted imaging (DWI) and its derivatives of diffusion tensor imaging and tractography, perfusion imaging, permeability imaging, MR angiography (MRA), and functional MRI (fMRI). As the techniques of MR become more precise, there is corresponding need for increased accuracy and the tracking of the patient during the MR procedure. See E. Fukushima and S. B. W. Roeder, Experimental Pulse NMR Addison-Wesley, Reading, M A 1981; T. C. Farrar, An Introduction To Pulse NMR Spectroscopy Farragut Press, Chicago, 1987; R. C. Jennison, Fourier Transforms and Convolutions Pergamon Press, NY 1961; E. O. Brigham, The Fast Fourier Transform Prentice-Hall, Englewood Cliffs, N.J. 1974; and A. Carrington A. D. McLachlan, Introduction To Magnetic Resonance Chapman and Hall, London 1967 which are each hereby incorporated by reference.
Functional MRI (fMRI) measures signal changes in the brain that are due to changing neural activity. This scan is completed at a low resolution but at a very rapid rate (typically once every 1-3 seconds). Increases in neural activity cause changes in the MR signal via a mechanism called the BOLD (blood oxygen level-dependent) effect. Increased neural activity causes a corresponding increased demand for oxygen, which is responded to by the vascular system, which increases the amount of oxygenated relative to deoxygenated hemoglobin. Because deoxygenated hemoglobin attenuates the MR signal, the vascular response leads to a signal increase that is related to the neural activity. The use of MRI to measure physiologic and metabolic properties of tissue non-invasively requires dynamic imaging to obtain time-series data.
One example of the use of fMRI is to measure brain activity. This use relies on a well-established neurovascular coupling phenomenon that results in transient increases in blood flow, oxygenation, and volume in the vicinity of neurons that are functionally activated above their baseline level. Signal changes due to the blood oxygenation-level-dependent (BOLD) effect are intrinsically weak (only several percent signal change from baseline at 4.0 T or less). In addition, as BOLD imaging is typically coupled with a repetitive behavioral task (e.g., passive sensory, cognitive, or sensorimotor task) to localize BOLD signals in the vicinity of neurons of interest, there is significant potential for fMRI to be confounded by the presence of small head motions. Specifically, such motion can introduce a signal intensity fluctuation in time due to intra-voxel movement of an interface between two different tissues with different MR signal intensities, or an interface between tissue and air. Random head motion decreases the statistical power with which brain activity can be inferred, whereas task-correlated motion cannot be easily separated from the fMRI signal due to neuronal activity, resulting in spurious and inaccurate images of brain activation. In addition, head motion can cause mis-registration between neuroanatomical MR and fMR images that are acquired in the same examination session. This latter point is important because the neuroanatomical MRI data serve as an underlay for fMRI color maps, and mis-registration results in mis-location of brain activity. An analogous problem exists for aligning anatomical and functional MR images performed on different days.
Lack of motion in current MRI examinations anatomic motion is not merely preferred, but is instead absolutely essential. Most aspects of human motor system performance require the patient to execute a movement as part of the behavioral task that is imaged to visualize brain activity. Movements can be very simple (e.g., self-paced finger tapping) or more complex (e.g., visually-guided reaching). Such examinations require both that the desired movement is performed in a well-controlled or well-quantified fashion, and also that the movement does not induce task-correlated head motion that confounds the ability to observe brain activity using fMRI. Perhaps the most complicated scenario involves combining use of virtual reality (VR) technology with fMRI, to determine brain activity associated with VR tasks for assessment and rehabilitation of impaired brain function. Such applications are important from the standpoint of “ecological validity” as they provide the opportunity to visualize brain activity associated with tasks that generalize well to everyday behavior in the real 3D-world. For example, position tracking would be required to provide realistic visual representation of a virtual hand operated by a data glove in a virtual environment.
The problem of motion tracking within an fMRI environment has been well documented in published medical literature describing various aspects of motion detection and quantitation. See Seto et al., NeuroImage 2001, 14:284-297; Hajnal et al., Magn Res Med 1994, 31: 283-291; Friston et al., Magn Res Med 1996, 35:346-355; Bullmore et al., Human Brain Mapping 1999, 7: 38-48; Bandettini et al., Magn Res Med 1993, 30:161-173; Cox. Comp Med Res 1996, 29:162-173; Cox et al., Magn Res Med 1999, 42:1014-1018; Grootoonk et al., NeuroImage 2000, 11:49-57; Freire et al., IEEE Trans Med Im 2002, 21(5):470-484; Babak et al., Magn Res Im 2001, 19:959-963; Voklye et al. 1999, Magn Res Med 41:964-972, which are each incorporated by reference.
As the clinical applications of MRI expand, there is a concurrent requirement for improved technology to visualize and determine the position and orientation of moving objects in the imaging field. Improvements in position tracking technology are required to advance the resolution and quality of the MRI, including the ability to image the anatomy of a patent, the imaging of tissue functions, the use of MRI data for other imaging modalities, and interventional applications.
For anatomical and functional MRI applications, as well as interventional MRI, there is the additional need to register data from other imaging modalities to provide comprehensive and complementary anatomical and functional information about the tissue of interest. The registration is performed either to enable different images to be overlaid, or to ensure that images acquired in different spatial formats (e.g., MRI, conventional x-ray imaging, ultrasonic imaging) can be used to visualize anatomy or pathology in precisely the same spatial location. While some algorithms exist for performing such registrations, computational cost would be significantly reduced by developing technology that enables data from multiple different imaging modalities to be inherently registered by measuring the patient's orientation in each image with respect to a common coordinate system.
By detecting, tracking, and correcting for changes in movement, data acquisition can be synchronized to a specific target. As a consequence, MR data acquisition is gated to a specific position of the target, and by implication, to a specific position of a specific target region.
U.S. Pat. No. 6,067,465 to Foo, et al. discloses a method for detecting and tracking the position of a reference structure in the body using a linear phase shift to minimize motion artifacts in magnetic resonance imaging. In one application, the system and method are used to determine the relative position of the diaphragm in the body in order to synchronize data acquisition to the same relative position with respect to the abdominal and thoracic organs to minimize respiratory motion artifacts. The time domain linear phase shift of the reference structure data is used to determine its spatial positional displacement as a function of the respiratory cycle. The signal from a two-dimensional rectangular or cylindrical column is first Fourier-transformed to the image domain, apodized or bandwidth-limited, converted to real, positive values by taking the magnitude of the profile, and then transformed back to the image domain. The relative displacement of a target edge in the image domain is determined from an auto-correlation of the resulting time domain information.
There is often a need in neuroimaging to look for changes in brain images over long periods of time, such as the waxing and waning of MS lesions, progressive atrophy in a patient with Alzheimer's disease, or the growth or remission of a brain tumor. In these cases, the ability to determine the position of anatomy as a function of time is extremely important to detect and quantify subtle changes. High-spatial resolution is a basic requirement of 3D brain imaging data for patients with neurological disease, and motion artifacts a consequence of movement during scanning pose a significant problem. If a patient does not stay completely still during MR neuroimaging the quality of the MR scan will be compromised.
Many of the advantages of MRI that make it a powerful clinical imaging tool are also valuable during interventional procedures. The lack of ionizing radiation and the oblique and multi-planar imaging capabilities are particularly useful during invasive procedures. The absence of beam-hardening artifacts from bone allows complex approaches to anatomic regions that may be difficult or impossible with other imaging techniques such as conventional CT. Perhaps the greatest advantage of MRI is the superior soft-tissue signal contrast available, which allows early and sensitive detection of tissue changes during interventional procedures.
MR is used for procedures such as “interventional radiology”, where images produced by an MRI scanner guide surgeons in a minimally invasive procedure. However, the non-magnetic environment required by the scanner, and the strong magnetic radiofrequency and quasi-static fields generated by the scanner hardware require the use of specialized instruments. Exemplary of such endoscopic treatment devices are devices for endoscopic surgery, such as for laser surgery disclosed in U.S. Pat. No. 5,496,305 to Kittrell et al, and biopsy devices and drug delivery systems, such as disclosed in U.S. Pat. No. 4,900,303 and U.S. Pat. No. 4,578,061 to Lemelson.
Prior art attempts at tracking motion using cross-correlation and other simple distance measurement techniques have not been highly effective where signal intensities vary either within images, between images, or both. U.S. Pat. No. 6,292,683 to Gupta et al. discloses a method and apparatus to track motion of anatomy or medical instruments between MR images. The invention includes acquiring a time series of MR images of a region of interest, where the region of interest contains the anatomy or structure that is prone to movement, and the MR images contain signal intensity variations. The invention includes identifying a local reference region in the region of interest of a reference image and acquired from the time series. The local reference region of the reference image is compared to that of the other MR images and a translational displacement is determined between the local reference region of the reference image and of another MR image. The translational displacement has signal intensity invariance and can accurately track anatomy motion or the movement of a medical instrument during an invasive procedure. The translational displacement can be used to align the images for automatic registration, such as in myocardial perfusion imaging, MRA, fMRI, or in any other procedure in which motion tracking is advantageous. One of the problems with this invention, is that the application and implementation of this methodology has proven difficult.
Two implementations of this correction scheme have been disclosed. The first is where a correlation coefficient is calculated and used to determine the translational displacement, and one in which the images are converted to a binary image by thresholding (using signal intensity thresholds) and after computation of a filtered cross-correlation, a signal peak is located and plotted as the translational displacement. Examples of techniques using this approach are shown in U.S. Pat. No. 5,947,900 (Derbyshire) and U.S. Pat. No. 6,559,641 (Thesen)
U.S. Pat. No. 6,516,213 to Nevo discloses a method and apparatus to determine the location and orientation of an object, while the body is being scanned by magnetic resonance imaging (MRI). Nevo estimates the location and orientation of various devices (e.g., catheters, surgery instruments, biopsy needles) by measuring voltages induced by time-variable magnetic fields in a set of miniature coils, said time-variable magnetic fields being generated by the gradient coils of an MRI scanner during its normal imaging operation. However, unlike the present invention, the system disclosed by Nevo is not capable of position tracking when imaging gradients are inactive, nor is it capable of measurements outside the sensitive volume of the imaging gradients.
A subset of all of the above correction schemes is currently conventionally employed in fMRI. As in anatomical MRI, these schemes remain an incomplete solution to the problem and the search for improved motion suppression continues. Typically, fast imaging is employed to “freeze” motion within the fMRI acquisition time frame, in combination with use of head restraints to limit motion. It is still possible to achieve poor activation image quality if patients exhibit task-correlated motion on the order of 1 millimeter. This problem is particularly manifest in specific patient populations (e.g. dementia, immediate post-acute phase of stroke). Furthermore, image-based coregistration algorithms suffer from methodological limitations. Consequently, the resulting co-registered images still can suffer from residual motion contamination that impairs the ability to interpret brain activity.
Another method of tracking the position of a patient in an MRI is disclosed in US Application 2005/0054910, published Mar. 10, 2005. In this approach, a reference tool is fixed to a stationary target as close as possible to the centre of the sensitive measuring volume of an MRI-compatible camera system. There are several drawbacks of this approach, including the requirement of a second “tracking” component that must be calibrated with a dummy object, the position ambiguity due to the configuration of this approach, and the inherent limitation of the resolution provided by this approach.
U.S. Pat. No. 6,879,160 to Jakab describes a system for combining electromagnetic position and orientation tracking with magnetic resonance scanner imaging. Jakab discloses a system where the location of a magnetic field sensor relative to a reference coordinate system of the magnetic resonance scanner is determined by a tracking device using a line segment model of a magnetic field source and the signal from a magnetic field sensor. However, resolutions provided by the Jakab invention are not as precise as is possible.
There is consequently a need for improved patient movement tracking techniques in medical imaging. There is a need for improved patient movement tracking that can function in adverse environments including high strength magnetic and/or radio frequency fields without the tracking mechanism exerting it's own RF pulse or magnetic field. There is a need for improved patient movement tracking techniques that can be performed in real time. In particular, but without limitation, there is a need for real time tracking of a patient's head position in a high field strength fMRI without disrupting the scanning by the fMRI.